The field of the invention is systems and methods for magnetic resonance spectroscopy (MRS) and magnetic resonance imaging (MRI). More particularly, the invention relates to systems and methods for correcting spectroscopic data for errors arising from phase offsets and time delays.
When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the excited nuclei in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) that is in the x-y plane and that is near the Larmor frequency, the net aligned moment, Mz, may be rotated, or “tipped”, into the x-y plane to produce a net transverse magnetic moment Mxy. A signal is emitted by the excited nuclei or “spins”, after the excitation signal B1 is terminated, and this signal may be received and processed to form an image.
When utilizing these “MR” signals to produce images, magnetic field gradients (Gx, Gy and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received MR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
The measurement cycle used to acquire each MR signal is performed under the direction of a pulse sequence produced by a pulse sequencer. Clinically available MR systems store a library of such pulse sequences that can be prescribed to meet the needs of many different clinical applications. Research MR systems include a library of clinically proven pulse sequences and they also enable the development of new pulse sequences.
Magnetic resonance spectroscopy (MRS) is based on collecting and analyzing a radiofrequency signal that is produced from the relaxation of excited protons or other spin species, including those that are bound to various chemical compounds. As the spin species relax back to their baseline (i.e., lower) energy state, they emit radiofrequency waves that are detected by the MRS system. The amplitude of each detected signal is indicative of the amount of the particular spin species (or chemical compound) present, while the frequency of each signal is indicative of the chemical structure of the spin species (or chemical compound) and its surrounding environment. Initially, these emitted signals are in phase, even if they originate from different chemical compounds. However, because the emitted signals exhibit different frequencies, they rapidly become out of phase with each other. Furthermore, during the acquisition of data with a magnetic resonance (MR) system, errors arise due to the inexact nature of the electronic equipment, the distance from the volume of interest (VOI) to the detector, differences in the T2 decay times of the different spin species (or chemical compounds), the size of the VOI, and the off-center location of the VOI relative to the MR detector system. For example, a time delay between when a signal begins to be emitted and the time that the electronic equipment begins to detect the signal can be present in the acquired data. These errors are prone to cause differences in the time delay between the excitation of the sample, called the “zero time”, and the acquisition of the emitted signal. Therefore, as a result of these errors, each sample of data has a different initial phase offset and time delay. These time and phase differences present problems when averaging data samples from different sets in order to increase signal-to-noise ratio (SNR).
Typically, MRS is used to generate a one-dimensional frequency spectrum representing the presence of certain chemical bonds in the region of interest. In medical diagnosis and treatment, MRS provides a non-invasive means of identifying and quantifying metabolites from a region of interest, often the human brain. By finding the relative spectral amplitudes resulting from frequency components of different molecules, medical professionals can identify chemical species and metabolites indicative of diseases, disorders, and other pathologies such as Alzheimer's disease, cancer, stroke, and the like. In this context, two nuclei are typically of particular interest, 1H and 31P. Phosphorus-31 (31P) MRS is directed to the detection of compounds involved in energy metabolism relating to membrane synthesis and degradation. Metabolites of particular interest in proton MRS studies include glutamate (Glu), glutainine (Gln), choline (Cho), creatine (Cre), N-acetylasparate (NAA), and the inositols (ml and sl). With new contrast agents such as hyperpolarized carbon-13 (13C), metabolic processes can be observed in the human body. For example, in the context of cancer detection, the signal contributions from various metabolites can be analyzed in regions of interest. Also, much work has been done in cardiac energetics using 31P spectroscopy.
Over the past two decades, many fast MR spectroscopic imaging techniques have been developed; among them, multiple spin-echo acquisition, echo-planar spatial encoding, and spiral readout. Compared to the traditional chemical-shift imaging (CSI) technique, these methods offer 2- to 4-fold accelerations in data acquisition time. By contrast, Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) can accelerate data acquisition by an order of magnitude using echo-planar readouts to collect spectral and 1-dimensional spatial information. The PEPSI technique has been developed for clinical MR scanners to measure 2D and 3D metabolite distributions in several minutes and with high spatial resolution. Given its benefit of fast acquisition, the PEPSI technique has already been employed in many clinical MRS studies.
In conventional MRS applications, the signal-to-noise ratio (SNR) is rather low in the acquired spectroscopic data. This can be improved, in general, by using larger samples of data; however, often one also wants to compare brain chemicals from two small volumes of interest. As such, the most common approach to increasing the SNR of spectroscopic data is to sample multiple signals within a defined volume of interest. Furthermore, the SNR can be additionally improved by averaging the samples together.
There are commonly two ways of producing spectra from multi-sample data sets. One is to average the time sampled data first and subsequently Fourier transform (FT) the result when applied to a single data set. The other common method is to FT the individual time samples first, followed by taking the FT of the result. Since the FT is linear, both of these methods give the same result; however, because it is easier to add values together than FT, the first method is usually employed, in which averaged time sample data is transformed. A typical procedure is to collect 16 sets of 16 averaged samples for a total of 256 individual samples. Unfortunately, the assumption that such data sets combine by simple averaging is flawed. In general, this is due to two factors.
First, when a spin species is excited and is located at the center of the VOI, the emitted signal is at its maximum and the signals from all the nuclei are in phase. However, there is a delay time between the excitation of the nuclei and the sampling of the first emitted RF wave due to limitations in the electronic circuits. During this delay, the signals from the spin species at different frequencies fall out of phase and no longer add coherently. In addition, the time delay also causes loss of the signal that is emitted during the time period corresponding to the delay. Moreover, the physical distance between the VOI and the detector also results in the signals from different frequencies arriving at the detector with different phases. The duration of time between excitation and acquisition of the first data sample is unknown and can vary between data sets. As a result, the initial phase of each excitation is unknown and varies unpredictably with each excitation. Only at the initial moment of excitation are all of the emitted signals from the spin species in phase. Second, the T2 decay times of the different spin species often differ and their apparent relative concentrations change over time. As a result, each time sample that is acquired has a slightly different starting time and an arbitrary phase. If the phase and starting times could be made to match, then the spectra could be produced without T2 decay and with all the peaks in phase and at their maximal amplitude.
Further difficulties in producing the spectrum from the data include the situation in which the sample that produces the detected RF signal might not be exactly at the isocenter of the detector system. Instead, the sample might be off the plane of the detector, or in the plane but not on the isocenter of the detectors. Additionally, the detector system itself might be out of calibration. Either of these situations could lead to the detection of waves by the real and imaginary channels that are slightly out of the usual 90 degree phase difference relative to each other.
Because the detectors are generally not sitting exactly at their isocenter the emitted RF waves of two different frequencies will, in general, arrive at the detector with a phase shift relative to the other emitted wave. Since the detectors cannot be at the isocenter, there will always be a phase shift of the waves of one frequency relative to others. Immediately after excitation, the waves emitted from the nuclei are all in phase; however, for each excitation-emission event, the initial phase is random and unknown. Moreover, there is often times a slight time delay between exciting the nuclei and detecting the first signal. In this duration of time, rapid T2 decay effects will result in a loss of signal. This time delay is unknown and might not be consistent between different data acquisition events.